Related papers: Web Spam Detection Using Multiple Kernels in Twin …

Spam pages are designed to maliciously appear among the top search results by excessive usage of popular terms. Therefore, spam pages should be removed using an effective and efficient spam detection system. Previous methods for web spam…

Web spam refers to some techniques, which try to manipulate search engine ranking algorithms in order to raise web page position in search engine results. In the best case, spammers encourage viewers to visit their sites, and provide…

Spam is commonly known as unsolicited or unwanted email messages in the Internet causing potential threat to Internet Security. Users spend a valuable amount of time deleting spam emails. More importantly, ever increasing spam emails occupy…

A robust and reliable system of detecting spam reviews is a crying need in todays world in order to purchase products without being cheated from online sites. In many online sites, there are options for posting reviews, and thus creating…

Support Vector Machines (SVMs) are among the most popular classification techniques adopted in security applications like malware detection, intrusion detection, and spam filtering. However, if SVMs are to be incorporated in real-world…

The rapid growth of electronic communication has necessitated more robust systems for email classification and sentiment detection. This study presents a comparative performance analysis between traditional machine learning algorithms and…

The Internet is used by billions of users every day because it offers fast and free communication tools and platforms. Nevertheless, with this significant increase in usage, huge amounts of spam are generated every second, which wastes…

Search engine became omnipresent means for ingoing to the web. Spamming Search engine is the technique to deceiving the ranking in search engine and it inflates the ranking. Web spammers have taken advantage of the vulnerability of link…

Support Vector Machines (SVMs) are powerful learners that have led to state-of-the-art results in various computer vision problems. SVMs suffer from various drawbacks in terms of selecting the right kernel, which depends on the image…

Machine learning algorithms are increasingly being applied in security-related tasks such as spam and malware detection, although their security properties against deliberate attacks have not yet been widely understood. Intelligent and…

We propose a new detection algorithm that uses structural relationships between senders and recipients of email as the basis for the identification of spam messages. Users and receivers are represented as vectors in their reciprocal spaces.…

In this paper, we present new optimization models for Support Vector Machine (SVM), with the aim of separating data points in two or more classes. The classification task is handled by means of nonlinear classifiers induced by kernel…

Web spam is a big problem for search engine users in World Wide Web. They use deceptive techniques to achieve high rankings. Although many researchers have presented the different approach for classification and web spam detection still it…

In the last decade we have witnessed the explosive growth of online social networking services (SNSs) such as Facebook, Twitter, RenRen and LinkedIn. While SNSs provide diverse benefits for example, forstering interpersonal relationships,…

Support vector machine (SVM), is a popular kernel method for data classification that demonstrated its efficiency for a large range of practical applications. The method suffers, however, from some weaknesses including; time processing,…

The purpose of this report is in examining the generalization performance of Support Vector Machines (SVM) as a tool for pattern recognition and object classification. The work is motivated by the growing popularity of the method that is…

Support vector machines (SVM) and other kernel techniques represent a family of powerful statistical classification methods with high accuracy and broad applicability. Because they use all or a significant portion of the training data,…

Due to the rapid growth in technology employed by the spammers, there is a need of classifiers that are more efficient, generic and highly adaptive. Neural Network based technologies have high ability of adaption as well as generalization.…

We give a new link spam detection and PageRank demotion algorithm called MaxRank. Like TrustRank and AntiTrustRank, it starts with a seed of hand-picked trusted and spam pages. We define the MaxRank of a page as the frequency of visit of…

In recent years, Cyber attacks have increased in number, and with them, the intensity of the attacks and their potential to damage the user have also increased significantly. In an ever-advancing world, users find it difficult to keep up…